Receiver Operating Characteristic Curves or ROC curves for short. These are classicaly a curve comparing the the True Positive Fraction (TPF) along the vertical or y-axis; and, the False Positive Fraction (FPF) along the horizontal or x-axis.
Diagnostic tests and tools may be compared by plotting their ROC curves for different threshold values of detection. It is generally argued that the greater the "area under the curve" the better the test is.
The ROC curve is drawn by testing a series of different threshold values for the TEST; and, plotting the True Positive Fraction (TPF) against the False Negative Fraction (FNF) for each threshold value.
"Localization Response" (LROC) curves measure the ability to detect AND localize the lesion targets.
"Free Resonse" (FROC) curves
"Alternative FROC" (AFROC) curves
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=8946368

Receiver Operating Characteristic Curves or ROC curves for short. These are classicaly a curve comparing the the True Positive Fraction (TPF) along the vertical or y-axis; and, the False Positive Fraction (FPF) along the horizontal or x-axis.
Diagnostic tests and tools may be compared by plotting their ROC curves for different threshold values of detection. It is generally argued that the greater the "area under the curve" the better the test is.
The ROC curve is drawn by testing a series of different threshold values for the TEST; and, plotting the True Positive Fraction (TPF) against the False Negative Fraction (FNF) for each threshold value.
"Localization Response" (LROC) curves measure the ability to detect AND localize the lesion targets.
"Free Resonse" (FROC) curves
"Alternative FROC" (AFROC) curves
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=8946368